EP 3662418 A1 20200610 - METHOD AND DEVICE FOR MACHINE LEARNING IN A COMPUTING UNIT
Title (en)
METHOD AND DEVICE FOR MACHINE LEARNING IN A COMPUTING UNIT
Title (de)
VERFAHREN UND VORRICHTUNG FÜR MASCHINELLES LERNEN IN EINER RECHENEINHEIT
Title (fr)
PROCÉDÉ ET DISPOSITIF DESTINÉS À L'APPRENTISSAGE AUTOMATIQUE DANS UNE UNITÉ DE CALCUL
Publication
Application
Priority
EP 2017078534 W 20171108
Abstract (en)
[origin: WO2019091551A1] The invention relates to a method and to a device for machine learning. In order to create favorable method conditions, according to the invention, an at least first machine learning model (8) is trained by means of an at least first data set (3), a second machine learning model (9) is trained by means of a second data set (4), an at least first prediction data set (12) is formed by means of the trained, at least first machine learning model (8), a second prediction data set (13) is formed by means of the trained second machine learning model (9), a linking machine learning model (15) is trained at least by means of the first prediction data set (12) and the second prediction data set (13), a third prediction data set (14) is formed by means of the linking machine learning model (15), and controlled variables for controlling a control apparatus (2) are formed at least by means of the third prediction data set (14). Thus, the demand for computing power is reduced and the prediction accuracy and control accuracy are increased.
IPC 8 full level
G06N 99/00 (2019.01); G05B 13/02 (2006.01); G06N 3/04 (2006.01)
CPC (source: EP US)
G05B 13/0265 (2013.01 - EP); G06N 5/04 (2013.01 - US); G06N 20/00 (2018.12 - EP US); G06N 3/045 (2023.01 - EP)
C-Set (source: US)
Citation (search report)
See references of WO 2019091551A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated extension state (EPC)
BA ME
DOCDB simple family (publication)
WO 2019091551 A1 20190516; CN 111328401 A 20200623; CN 111328401 B 20231010; EP 3662418 A1 20200610; EP 3662418 B1 20210825; US 11488035 B2 20221101; US 2021192368 A1 20210624
DOCDB simple family (application)
EP 2017078534 W 20171108; CN 201780096654 A 20171108; EP 17807715 A 20171108; US 201716761851 A 20171108